2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
455
4 - The Impact Of Data Quality: A Study On The Coast Guard’s Data
Nelson Christie, Rutgers University, Princeton, NJ, 08540, United
States,
We report our findings with the US Coast Guard on a project designed to
identifying errors in a large operational database. We combined interview results
with statistical algorithms to identify a large number of errors in the data. We
then examine the impact that data quality has on operational planning.
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Broadway C-Omni
Large-Scale Optimization in Transportation
Sponsored: TSL, Intelligent Transportation Systems (ITS)
Sponsored Session
Chair: Velibor Misic, Massachusetts Institute of Technology,
Massachusetts Avenue, Cambridge, MA, 02139, United States,
1 - Planning Optimization For Integrated Transportation Systems
Bradley Sturt, Massachusetts Institute of Technology,
Massachusetts Avenue, Cambridge, MA, 02139, United States,
Dimitris Bertsimas, Sebastien Martin, Yee Sian Ng,
Julia Yan
Passengers move through large cities via various public transportation systems,
such as subway and bus systems. City operators need to decide how to schedule
the trains and buses throughout the day. Prior work has addressed making the
decisions for each transportation system in isolation, which may result in a
suboptimal citywide transportation system. This work proposes an optimization
approach for holistically and cooperatively optimizing the decisions for decision
makers for the subway, bus systems and the city.
2 - From Physical Properties Of Transportation Flows To Demand
Predictions: An Optimization Approach
Julia Y. Yan, Massachusetts Insitute of Technology, Massachusetts
Avenue, Cambridge, MA, 02139, United States, ,
Dimitris Bertsimas
Transportation system management requires accurate demand data. The main
data sources are often aggregated datasets such as entry/exit data, and one must
recover the original demand. Such problems are generally underspecified. We
present an optimization framework to recover origin-destination matrices under
minimal assumptions, enforcing reasonable physical constraints such as flow
conservation, smoothness, and sparsity. We evaluate this on real-world datasets
and show 6-7% improvement in R2 over a baseline.
3 - Online Taxi Routing In New York City
Sebastien Martin, Massachusetts Institute of Technology,
Massachusetts Avenue, Cambridge, MA, 02139, United States,
, Dimitris Bertsimas, Patrick Jaillet
Taxi dispatching used to have little room for optimization. However, more and
more customers request cabs from their cellphone. This gives transportation
network companies prior information that can be leveraged to achieve a better
efficiency. Large-scale taxi routing has usually been done with simple rules or
heuristics. Our work proposes ways to scale optimization-based online routing
algorithms to the largest instances of vehicle routing with real data. We use
historical taxi trip data in New York City to dispatch in real time thousands of
taxis and serve tens of thousands of customers.
4 - A Modern Optimization Approach To The Airlift Planning Problem
For The United States Transportation Command (USTRANSCOM)
Velibor Misic, Massachusetts Institute of Technology,
Massachusetts Avenue, Cambridge, MA, 02139, United States,
Dimitris Bertsimas, Allison An Chang,
Nishanth Mundru
USTRANSCOM plans missions globally, the majority traveling by air. These
missions are challenging to plan due to their combinatorial nature and complex
constraints. We propose a novel solution approach that combines local search,
mixed-integer optimization and column generation, and show that it provides
high quality solutions. This material is based upon work supported by
USTRANSCOM under Air Force Contract No. FA8721-05-C-0002. Any opinions,
findings, conclusions or recommendations expressed in this material are those of
the authors and do not necessarily reflect the views of USTRANSCOM.
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Broadway D-Omni
Health Care, Modeling XV
Contributed Session
Chair: Shanshan Wang, PhD Candidate, Beijing Institute of Technology,
5 southstreet Zhongguancun, Haidian District, Beijing, 100081, China,
1 - Safety Stock For Blood Products With Short Shelf Life
Christine Pitocco, Research Professor, Stony Brook University, 202
Harriman Hall, Harriman Hall Room 202, Stony Brook, NY, 11794-
3775, United States,
Katsunobu Sasanuma
Poorly managed inventory of apheresis platelets in a blood bank can result in a
loss of revenue and safety issues for patients in need. A safety stock of platelets
must be available, but higher levels of safety stock may cause wastage if not
utilized. We discuss how the safety stock level should change according to the
change in demand and shelf life. We propose an optimal inventory control policy
based on a simulation of blood bank operations.
2 - Facility Location Problem For Stochastic Mixed-integer
Programming In Healthcare
Mengnan Chen, University of Central Florida, 12800 Pegasus
Drive, PO Box 162993, Orlando, FL, 32816-2993, United States,
, Qipeng Zheng
This paper considers a facility location problem with patients’ appointment and
physician scheduling. We model this problem as a two-stage optimization
problem. In the first stage, depending on the patients’ choices, which is relative to
their characteristics and physicians/clinics’ attributes, physicians will be scheduled
to the different clinics. In the second stage, the central hospital will match
patients’ choices and physicians’ scheduling. Using discrete choice model, we
estimate the probability for patient’s choice. Let the scenario is the different
combination of patients’ choices, then we can develop a stochastic mixed-integer
programming to solve the facility location problem.
3 - Test Modality Capacity Simulation: A Nuclear Medicine
Radiology Assessment
Haris Ackerman, Management Engineer, Virtua Health,
303 Lippincott Drive, Marlton, NJ, 08053, United States,
Mojisola Otegbeye, Hala Sweidan
Significant delays in the nuclear medicine radiology department of a 433 bed
acute-care hospital increases patient length of stay resulting in patient
dissatisfaction and reduced reimbursement rates. Simulation modeling deployed
to show a budget neutral increase in daily stress test fulfillment rate from 80% to
99.9% while maintaining current staffing roster by utilizing optimal staff
scheduling patterns.
4 - Outpatient Appointment Scheduling And Sequencing Model With
Uncertain Service Time And Correlation
Shanshan Wang, PhD Candidate, Beijing Institute of Technology,
5 Southstreet Zhongguancun, Haidian District, Beijing, 100081,
China, , Jinlin Li, Chun Peng
As the window of hospital, outpatient appointment scheduling and sequencing
plays a critical role in the allocation of healthcare resources. We take different jobs
and uncertain service time into consideration. Based on support and moment of
service time distribution, we employ mean absolute deviation to capture its
correlation, propose distributionally robust models, and can be reformulated them
as tractable counterparts. Numerical results show that when sequence is fixed, it’s
optimal to allocate time allowances with a decreasing pattern. When considering
“New” and “Repeat” patients, optimal outpatient sequence of repeat patients is in
the front of new patients.
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